SOTAVerified

Question Answering

Question answering can be segmented into domain-specific tasks like community question answering and knowledge-base question answering. Popular benchmark datasets for evaluation question answering systems include SQuAD, HotPotQA, bAbI, TriviaQA, WikiQA, and many others. Models for question answering are typically evaluated on metrics like EM and F1. Some recent top performing models are T5 and XLNet.

( Image credit: SQuAD )

Papers

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Showing 226–250 of 10817 papers

TitleStatusHype
KnowTrace: Bootstrapping Iterative Retrieval-Augmented Generation with Structured Knowledge TracingCode1
DGRAG: Distributed Graph-based Retrieval-Augmented Generation in Edge-Cloud Systems—0
BizFinBench: A Business-Driven Real-World Financial Benchmark for Evaluating LLMsCode0
ALAS: Measuring Latent Speech-Text Alignment For Spoken Language Understanding In Multimodal LLMs—0
MASKSEARCH: A Universal Pre-Training Framework to Enhance Agentic Search CapabilityCode2
VTool-R1: VLMs Learn to Think with Images via Reinforcement Learning on Multimodal Tool UseCode2
Hypercube-RAG: Hypercube-Based Retrieval-Augmented Generation for In-domain Scientific Question-AnsweringCode0
ActiveDPO: Active Direct Preference Optimization for Sample-Efficient Alignment—0
Weaver: Interweaving SQL and LLM for Table Reasoning—0
SpokenNativQA: Multilingual Everyday Spoken Queries for LLMs—0
InfoChartQA: A Benchmark for Multimodal Question Answering on Infographic ChartsCode3
Are Vision Language Models Ready for Clinical Diagnosis? A 3D Medical Benchmark for Tumor-centric Visual Question AnsweringCode1
Medical Large Vision Language Models with Multi-Image Visual AbilityCode0
UNCERTAINTY-LINE: Length-Invariant Estimation of Uncertainty for Large Language Models—0
Self-Critique Guided Iterative Reasoning for Multi-hop Question AnsweringCode0
GC-KBVQA: A New Four-Stage Framework for Enhancing Knowledge Based Visual Question Answering Performance—0
SATORI-R1: Incentivizing Multimodal Reasoning with Spatial Grounding and Verifiable RewardsCode1
SituatedThinker: Grounding LLM Reasoning with Real-World through Situated ThinkingCode0
When Two LLMs Debate, Both Think They'll Win—0
The Silent Saboteur: Imperceptible Adversarial Attacks against Black-Box Retrieval-Augmented Generation Systems—0
Climate-Eval: A Comprehensive Benchmark for NLP Tasks Related to Climate Change—0
Multilingual Question Answering in Low-Resource Settings: A Dzongkha-English Benchmark for Foundation ModelsCode0
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation—0
BRIT: Bidirectional Retrieval over Unified Image-Text Graph—0
Scaling Up Biomedical Vision-Language Models: Fine-Tuning, Instruction Tuning, and Multi-Modal LearningCode4
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All datasetsSQuAD2.0SQuAD1.1HotpotQAPIQABoolQCOPATriviaQASQuAD1.1 devNatural QuestionsOpenBookQATruthfulQAMultiRC

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1IE-Net (ensemble)EM90.94—Unverified
2FPNet (ensemble)EM90.87—Unverified
3IE-NetV2 (ensemble)EM90.86—Unverified
4SA-Net on Albert (ensemble)EM90.72—Unverified
5SA-Net-V2 (ensemble)EM90.68—Unverified
6FPNet (ensemble)EM90.6—Unverified
7Retro-Reader (ensemble)EM90.58—Unverified
8EntitySpanFocusV2 (ensemble)EM90.52—Unverified
9TransNets + SFVerifier + SFEnsembler (ensemble)EM90.49—Unverified
10EntitySpanFocus+AT (ensemble)EM90.45—Unverified